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🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
ChatGLM-6B: An Open Bilingual Dialogue Language Model | 开源双语对话语言模型
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
Graph Neural Network Library for PyTorch
Convert Machine Learning Code Between Frameworks
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Perform data science on data that remains in someone else's server
GLM-4 series: Open Multilingual Multimodal Chat LMs | 开源多语言多模态对话模型
Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
An open-source framework for machine learning and other computations on decentralized data.
Benchmark datasets, data loaders, and evaluators for graph machine learning
The WeightWatcher tool for predicting the accuracy of Deep Neural Networks
YaRN: Efficient Context Window Extension of Large Language Models
A simple and extensible library to create Bayesian Neural Network layers on PyTorch.
Python implementation of Empirical Mode Decompoisition (EMD) method
This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL.
Federated Optimization in Heterogeneous Networks (MLSys '20)
Implementation of Electric Load Forecasting Based on LSTM(BiLSTM). Including Univariate-SingleStep forecasting, Multivariate-SingleStep forecasting and Multivariate-MultiStep forecasting.
Some GNNs are implemented using PyG for node classification tasks, including: GCN, GraphSAGE, SGC, GAT, R-GCN and HAN (Heterogeneous Graph Attention Network), which will continue to be updated in t…
PyTorch implementation of FedProx (Federated Optimization for Heterogeneous Networks, MLSys 2020).
Implementation of Electric Load Forecasting Based on LSTM (BiLSTM). Including direct-multi-output forecasting, single-step-scrolling forecasting, multi-model-single-step forecasting, multi-model-sc…
Implementation of cats-vs-dogs based on CNN.
PyTorch implementation of FedPer (Federated Learning with Personalization Layers).
PyTorch implementation of SCAFFOLD (Stochastic Controlled Averaging for Federated Learning, ICML 2020).
PyG implementation of GCN (Semi-Supervised Classification with Graph Convolutional Networks, ICLR 2017).Datasets: CiteSeer, Cora, PubMed, NELL.